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bert-wiki-choked – AI Model by hopkins | AlphaNeural AI

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hopkins/
bert-wiki-choked

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text-generation

generated_from_trainer

autotrain_compatible

endpoints_compatible

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bert-wiki-choked

This model is a fine-tuned version of bert-base-cased on the generator dataset.

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0005
train_batch_size: 128
eval_batch_size: 128
seed: 42
gradient_accumulation_steps: 8
total_train_batch_size: 1024
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 1000
num_epochs: 10
mixed_precision_training: Native AMP

Training results

Framework versions

Transformers 4.26.1
Pytorch 2.0.1+cu117
Datasets 2.12.0
Tokenizers 0.13.3